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Fast implementation of a l- l/1 penalized sparse representations algorithm: applications in image denoising and coding

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2 Author(s)
Jean-Jacques Fuchs ; IRISA/INRIA/Université de Rennes I, Campus de Beaulieu - 35042 Rennes Cedex - France. fuchs@irisa.fr ; Christine Guillemot

Sparse representation techniques have become an important tool in image processing in recent years, for coding, de-noising and in-painting purposes, for instance. They generally rely on an lscr2-lscr1 penalized criterion and fast algorithms have been proposed to speed up the applications. We propose to replace the lscr2-part of the criterion, which has been chosen both for its easy implementation and its relation to the PSNR quality measure, by a lscr-part. We present a new fast way to minimize a lscr- lscr1 penalized criterion and assess its potential benefits for image De-noising and coding.

Published in:

2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers

Date of Conference:

4-7 Nov. 2007